Electronic health record data holds great potential for conducting large, efficient randomised controlled trials. Despite progress towards greater availability of linked NHS datasets, the use of routine clinical data remains challenging for trialists. In this paper we describe the design, adaptations and implementation of methods for data collection and linkage in ARRISA-UK: a cluster-randomised controlled trial of a complex asthma management intervention involving 275 primary care practices across England, Wales and Scotland. Our methods were designed to build a dataset of linked primary care and secondary care data for approximately 10,000 'at-risk' asthma patients to measure the trial's primary outcome (asthma crisis events comprising respiratory-related hospital admissions, emergency department attendances and/or death for 'at-risk' asthma patients) and secondary clinical outcomes including the impact of the intervention on ∼180,000 asthma patients at participating practices. A high level of practice attrition (33%) was observed due to data extraction delays and technical barriers, patient identification errors, and concerns about the processing of patient identifiable data for the purpose of record linkage. We highlight the technical achievements, barriers and lessons learned from ARRISA-UK and propose recommendations to facilitate future data-enabled trials, including greater resourcing in recognition of their complex nature, improved systems of support and training in primary care, and the need to maintain and improve clinician and public trust in research data use for long term sustainability.

Background:Type 2 (T2) inflammation is increasingly recognised in COPD, though its immunopathological profile may differ from asthma. T2 inflammatory diseases often coexist, but their prevalence in COPD patients without asthma remains underexplored. This study investigated the prevalence of T2 inflammatory multimorbidities in individuals with COPD (without asthma) and compared it with those in people with asthma. It also examined the relationship between these multimorbidities and blood eosinophil counts (BEC). Methods:Using data from the Optimum Patient Care Research Database (OPCRD), we identified patients with COPD or asthma and assessed lifetime and adjusted prevalence of T2 comorbidities including allergic rhinitis, atopic dermatitis/eczema, nasal polyps, chronic rhinitis with or without polyps, eosinophilic oesophagitis and ulcerative colitis. Prevalence was stratified by BEC and adjusted for demographic and clinical variables. Results:Among 122 509 COPD and 1 154 094 asthma patients, T2 multimorbidities were present in both groups but significantly less common in COPD. Allergic rhinitis and nasal polyps were notably less prevalent in COPD, even at higher BEC levels. Prevalence of multimorbidities increased with BEC in both groups, with stronger associations observed for nasal polyps and ulcerative colitis. Eosinophilic oesophagitis was rare across both cohorts. Conclusion:T2 multimorbidities are present in COPD and their prevalence increases with BEC, though they are generally less prevalent than in asthma, suggesting distinct immunopathology.

Background:Lung cancer is significantly more common in patients with idiopathic pulmonary fibrosis (IPF) than the general population. Whether this risk extends to other fibrotic interstitial lung diseases (ILDs) including hypersensitivity pneumonitis (HP) and connective-tissue disease ILD (CTD-ILD), remains uncertain. We aimed to characterise lung cancer prevalence and incidence across ILDs. Methods:We conducted matched case-control and cohort analyses using the Optimum Patient Care Research Database. Adults with incident ILD were matched up to 1:4 to controls by age, sex and practice. Pre-existing lung cancer was examined using conditional logistic regression. Lung cancer incidence rates were analysed using Fine-Gray competing-risk models. Analyses were conducted overall and by ILD subtype. Findings:We evaluated 15 777 people with ILD (10 030 IPF, 4347 CTD-ILD, 1400 HP) and 62 417 controls. Prevalence of lung cancer at index date was 1.3% in ILD versus 0.4% in controls (OR 2.68, 95% CI 2.21-3.23). During follow-up (median 3.0 years, interquartile range 1.3-5.4), 540 (3.5%) ILD cases and 790 (1.3%) controls developed lung cancer. The incidence rate was 963.43 in ILD versus 367.57 in controls per 100 000 person-years with a sub-distributional hazard ratio (sHR) of 1.93 (95% CI 1.72-2.17). Lung cancer risk was elevated in cases with IPF (sHR 2.36, 95% CI 2.08-2.69) and CTD-ILD (sHR 1.78, 95% CI 1.48-2.14) but not HP. Findings were consistent in never-smokers. Interpretation:A strong relationship between ILD and lung cancer exists, with increased risk in CTD-ILD and IPF compared to the general population. Findings of this study support consideration of targeted lung cancer surveillance within ILD management paradigms.

BACKGROUND:The way in which risk predictors combine and contribute to severe asthma exacerbations may differ between clinical trials and real-world settings. RESEARCH QUESTION:How do the interactive pathways of risk predictors leading to severe asthma exacerbations compare under clinical trials vs real-world settings? STUDY DESIGN AND METHODS:The analysis involved 345 patients with severe asthma from the placebo arms of 2 international randomized controlled trials (RCTs), compared with 6,814 biologic-naïve patients from the International Severe Asthma Registry (ISAR). Sixteen key risk predictors, including demographics, biomarkers, lung function, health care use, exacerbation history, long-term oral corticosteroid use, asthma control, and nasal polyps, were covered. The outcome was the occurrence of severe asthma exacerbations over the 365 days after study enrollment. Bayesian networks (BNs), obtained from machine learning combined with expert knowledge, elucidated significant interplay processes of risk predictors that led to severe asthma exacerbations. External validation was performed in each cohort. RESULTS:The RCTs revealed 44 significant arcs (ie, probabilistic interdependency) between 16 risk factors, whereas the ISAR showed 170. Despite this difference, the main downstream prediction pathways were consistent across both settings, with 2 key pathways: total serum IgE level influenced blood eosinophils to predict future severe exacerbations, and severe exacerbation history directly predicted future severe exacerbations. In external validation, RCT-BN generalized well to ISAR patients (area under the receiver operating characteristic curve, 0.68), whereas ISAR-BN underperformed in RCT patients (area under the receiver operating characteristic curve, 0.50), and ISAR-BN demonstrated better calibration. INTERPRETATION:Our results show that the core pathways predicting severe asthma exacerbations were similar in both RCTs and real-world settings, with comparable predictive performance.

BACKGROUND:Severe asthma (SA) is associated with frequent exacerbations and high treatment costs. OBJECTIVES:To develop and validate an individualized risk calculator for severe exacerbations in SA, and evaluate its clinical utility for guiding personalized clinical decisions. METHODS:Patients with SA were identified from combined data from the International Severe Asthma Registry (2015-2022) and NOVEL observational longiTudinal studY (2016-2023) across 30 countries and regions. The prediction end point was the 12-month risk of 1 or more or 2 or more severe exacerbations. Using expert input and Bayesian network analysis, 11 routinely measured predictors were identified, measured within the past 12 months. A mixed-effects, zero-inflated negative binomial model was developed, adjusting for between-country variability and biologic drop-in effects. Internal-external cross-validation was performed using the natural clustering by country settings. RESULTS:Data from 9911 patients with SA were used. Essential predictors included age, sex, past 12-month severe exacerbations, asthma control, chronic rhinosinusitis, FEV1 to forced vital capacity ratio, percent predicted FEV1, blood eosinophils, fractional exhaled nitric oxide, and long-term oral corticosteroid and macrolide use. The model also adapted setting-specific baseline risks. In the internal-external cross-validation, across broad geographical and health care variability, the model showed excellent calibration and informative, generalizable discrimination (pooled area under the time-dependent receiver-operating characteristics curve of 0.63 [95% CI, 0.60-0.66] for ≥1 and 0.68 [95% CI, 0.64-0.72] for ≥2 exacerbations). Decision curve analysis showed clear net benefit across risk thresholds. CONCLUSIONS:The Risk of Exacerbation in Severe Asthma model quantifies SA exacerbation risk using routinely available predictors and demonstrates potential clinical utility.

BACKGROUND:There over 250 000 care home residents in England and they account for a disproportionate number of hospital admissions. Since 2016, enhanced services for care homes have been developed to reduce admissions but there is regional variation in provision. We used a nationally representative cohort of care home residents to identify predictors of admissions and measure regional risk adjusted variation. METHODS:Using primary care data from a third of practices in England, we derived a cohort of over 40 000 care home residents linked to the national regulator's register of care homes between 01/01/2023 and 31/12/2024. We estimated a three-level negative binomial regression model including resident, postcode district and commissioner (Integrated Care Board, ICB) level factors which predicted 6-monthly count of admissions. Using this model, we estimated funnel-plots to measure case-mix risk adjusted variation in admission rates at postcode district and commissioner geographical levels. RESULTS:Significant predictors of admission count included age, gender, frailty, presence of feeding tube, long-term catheterisation, polypharmacy, anticholinergic burden, sedative load, care home rating and proportion of care home jobs filled. Considerable variation in risk adjusted admission rates at commissioner (ICB) level was demonstrated. ICB outliers ranged between having 0.6 and 2.2 times as many admissions as would be expected based on case-mix. CONCLUSION:This is one of the largest studies of care home residents in England. We identified potentially modifiable risk factors for admissions and significant variation in ICB level admission rates. This variation could be the result of differences in enhanced services provision and requires further research.

Introduction:There is limited evidence on the impact of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) in patients with chronic obstructive pulmonary disease (COPD). Material and Methods:We conducted a retrospective matched cohort study including patients aged ≥40 years with COPD and T2D. Patients initiating GLP-1 RAs were matched 1:1 with GLP-1 naïve controls based on age, sex, smoking status, COPD treatment (LABA/LAMA/ICS), and exacerbation history. The index date was defined as the first GLP-1 RA prescription, control's index date was a COPD consultation within 186 days of matched patient index. The primary outcome was the number of COPD exacerbations during the 12 months following the index date. Secondary outcomes included oral corticosteroid (OCS) prescriptions and hospital resource utilization (HCRU). Poisson regression models adjusted for BMI and other confounders were used to estimate incidence rate ratios (IRR). Results:A total of 4479 matched patients were included. There were no significant differences between groups in exacerbation rates or OCS use in the year prior to the index date. During follow-up, patients treated with GLP-1 RAs had significantly fewer exacerbations (adjusted IRR [aIRR] 0.84, 95% CI: 0.79-0.89) and fewer OCS prescriptions (aIRR 0.86, 95% CI: 0.77-0.95) compared with controls. A significant delay in time to first OCS prescription was also observed. Conclusion:In this real-world cohort, initiation of GLP-1 RA treatment in patients with COPD and T2D was associated with lower COPD exacerbations and OCS use. These findings suggest a potential role for GLP-1 RAs in modifying the course of COPD in this comorbid population, warranting randomised trials.

Background:Cardiovascular diseases are prevalent in individuals with chronic obstructive pulmonary disease (COPD), but current cardiovascular risk assessment models are not optimised for COPD. We aimed to develop a prediction model for the 10-year risk of major adverse cardiovascular and respiratory events (MACRE) in patients with COPD. Methods:We used nationwide primary care electronic health records from individuals with COPD, aged ≥40 years in 2011 without prior myocardial infarction in the UK Optimum Patient Care Research Database. Practices were randomly divided at the practice level into derivation (80%) and validation (20%) datasets. The primary composite outcome (MACRE) consisted of myocardial infarction, coronary revascularization, heart failure, severe COPD exacerbation, and all-cause mortality. Multivariable Cox regression was used to derive the model using the derivation dataset, with the least absolute shrinkage and selection operator used for variable selection and shrinkage. Performance was evaluated using the validation dataset over prediction horizons of five and 10 years. Results:Among the 122,077 patients included (98,959 in the derivation set; whole cohort: 47.9% women and mean age 69.3 (SD 11.2) years), cardiometabolic risk factors were prevalent, and most had moderate (53.4%) or severe (24.7%) COPD. Over a median follow-up of 10.5 [interquartile range: 4.2-12.4] years, MACRE occurred in 50.2% of the validation set. Sixty-one predictor variables constituted the model, which demonstrated good-to-excellent discrimination and satisfactory calibration across prediction horizons (AUROC 0.78 at five years and 0.82 at 10 years, Brier score of 0.18 at five years and 0.16 at 10 years) in the validation set. Conclusion:A model derived using electronic medical records predicts MACRE in COPD with high discrimination and satisfactory calibration across medium and longer-term prediction horizons. Its utility to inform trial enrolment and clinical decisions requires further study.

Breathlessness is a common symptom linked to various respiratory and cardiac conditions, often causing delays in diagnosis and management in primary care. This study aimed to develop an algorithm using Bayesian Networks (BN) to predict ten conditions associated with presentations of breathlessness. The study included individuals aged 16 years and older with breathlessness recorded as the reason for visiting a general practitioner (GP) between 2002 and 2024 in 50 practices in the United Kingdom (UK). Thirty-four characteristics including demographic, symptoms, comorbidities and medication histories were considered as predictors. A total of 384,994 breathlessness episodes from 136,215 patients were analysed, with 55% being female and 42% aged over 60 years. The BN achieved good performance with area under the curve (ROC-AUC) values ranging from 0.68 for non-pneumonia lower respiratory tract infections (LRTI) to 0.94 for heart failure. The algorithm demonstrated strong predictive performance and could help GPs prioritise early and targeted diagnostic tests for the most likely causes of breathlessness, potentially reducing both diagnostic delays and costs.

RATIONALE:The clinical characteristics of persistent airflow limitation (PAL) were explored in patients aged ≥12 years with physician-assigned diagnoses of asthma, asthma plus chronic obstructive pulmonary disease (COPD), or COPD in the NOVEL Observational longiTudinal studY (NOVELTY) cohort. The NOVELTY study is a prospective study conducted in primary and secondary care in 18 countries. OBJECTIVES:To determine the proportion of patients with PAL at baseline, their baseline characteristics, and the stability and prognostic utility of PAL during follow-up. METHODS:PAL was defined as post-bronchodilator forced expiratory volume in 1 second/forced vital capacity (FEV1/FVC) ratio less than the lower limit of the normal range (European Respiratory Society [ERS]/American Thoracic Society [ATS]) or as <0.7 (Global Initiative for Chronic Obstructive Lung Disease [GOLD] criteria). RESULTS:We studied 9081 patients over 3 years (asthma: 4754; asthma + COPD; 1147; COPD: 3180). Baseline prevalence of PAL was 24.2% and 29.2% (asthma), 63.3% and 74.1% (asthma + COPD), and 65.4% and 75.8% (COPD) using ERS/ATS and GOLD criteria, respectively. Patients with PAL had markedly worse symptom burden and a history of more frequent moderate and severe exacerbations. In patients with asthma, PAL was associated with higher blood eosinophils and fractional exhaled nitric oxide (FeNO) values; 60% had never smoked. Of patients with PAL at baseline 84% continued to meet PAL criteria at Year 3. Irrespective of physician diagnosis, PAL was a marker of increased risk of moderate and severe exacerbations and poor symptom control during the 3-year follow-up. CONCLUSIONS:PAL is a stable trait associated with more severe disease and poor outcomes in adults with a physician-assigned diagnosis of asthma and/or COPD. CLINICAL TRIAL REGISTRATION (IF ANY):NOVELTY: NCT02760329.

Chronic respiratory diseases (CRDs) remain 1 of the leading causes of preventable morbidity and disability worldwide, affecting up to one-third of the total Western population in 2025. Recognizing the substantial burden of inflammatory airway diseases such as asthma, COPD, chronic rhinosinusitis, and respiratory allergy, the European Forum for Research and Education in Allergy and Airway Diseases (EUFOREA) organized the symposium "Shaping the Future of Respiratory Care" in April 2025 in Brussels, Belgium, at the occasion of the 10-year jubilee. Featuring keynote speakers from the World Health Organization and EUFOREA, this initiative had the following aims: (1) promoting dialogue on translating innovations into daily clinical practice; (2) encouraging collaboration between the different stakeholders in the respiratory field; and (3) defining strategic priorities to transform respiratory care and arrest the CRD epidemic over the next decade. The symposium highlighted the importance of moving toward predictive, preventive, and patient-centered medicine, while supporting value-based health care systems to improve long-term patient outcomes. This report summarizes the main insights and strategic directions discussed at the meeting.

Purpose:Chronic obstructive pulmonary disease (COPD) and its comorbidities impose substantial economic burdens on healthcare systems, but evidence remains scarce in Asian countries where patients exhibit distinct clinical and inflammatory phenotypes, as well as policy and health system differences. This study aimed to estimate direct medical costs of COPD multimorbidity, comparing to non-COPD patients in Singapore, and identify high-cost users. Patients and Methods:Using Singapore's health administrative data (2012-2019), we created a propensity score-matched COPD and non-COPD cohort and applied generalised linear models to estimate all-cause, index disease- and comorbidity-attributable costs. All costs were measured in patient-years (PYs) in 2023 Singaporean dollars (SGD$1=US$0.76=₤0.60=€0.69). Patient characteristics and comorbidity prevalence were compared across patients incurring top 10%, 11%-50%, and bottom 50% of average annualised costs. Results:The study included 18,866 patients from each group (83% males, 17% females). Average annual direct medical costs were significantly higher among COPD patients ($5,290.9/PY; 95% confidence interval [CI]: 5,242.9-5,350.1) than non-COPD patients ($1,110.4/PY; 95% CI: 1,085.9-1,135.9). 33.8% of total costs were COPD-attributable, with major contributions from other respiratory (15.0%), circulatory (14.9%), metabolic (7.8%), and digestive (4.7%) diseases. From 2012 to 2019, hospitalisation costs declined (-$59.0/year), while primary care (polyclinic) costs increased sharply (+$148.8/year). Indian patients comprised 67% of the top 10th cost percentile and experienced frequent hospitalisations (≥2/year). Conclusion:In Singapore's multi-ethnic Asian context, COPD patients incurred substantial multimorbidity costs, particularly from respiratory, circulatory, and metabolic diseases, underscoring distinct Asian multimorbidity patterns and highlighting the need for integrated, multimorbidity-focused care models. Disproportionately high costs among Indian patients and low female prevalence warrant further investigation.

IntroductionSupported self-management that includes a personalised asthma action plan and regular professional review, reduces unscheduled consultations, and improves asthma outcomes and quality of life. However, despite unequivocal inter/national guideline recommendations, supported self-management is poorly implemented in UK primary care. The IMPlementing IMProved Asthma self-management as RouTine (IMP2ART) implementation strategy (including facilitated provision of patient, professional, and organisational resources) has been developed to address this challenge and is being evaluated in a UK-wide cluster randomised controlled trial (cRCT). The internal pilot aimed to assess the trial recruitment processes, delivery of and general practice engagement with the implementation strategy to inform the progression criteria.MethodsUsing mixed methods, we recruited 12 general practices and monitored trial processes and IMP2ART delivery through team logs and automated data (e.g., use of patient online resources; uptake of practice education modules). Qualitative interviews with general practice staff and IMP2ART facilitators explored feasibility and acceptability of the implementation strategy.ResultsWe randomised 12 general practices to the IMP2ART implementation strategy arm (n = 6) or usual asthma care (control, n = 6). One control practice withdrew post-randomisation following concerns about data sharing. Most components were delivered successfully to the implementation group practices so that we met our progression criteria. In all six practices, the facilitated workshop was arranged within 12 weeks of randomisation and the team education module was completed (median 11 accesses/practice), the in-depth module was completed by 'the healthcare professional responsible for asthma reviews' (range 3-7 professionals/practice), and the asthma review template was successfully downloaded to the practice system. All six implementation practices received the baseline and first monthly audit and feedback report although there were delays in this process due to national-level governance changes. Practices' perceptions of IMP2ART were encouraging. In general, they participated in the patient, professional and organisational implementation strategies and reported positive experiences of the trial.ConclusionsThe study provides evidence that the IMP2ART trial is feasible, and the implementation strategy is acceptable with only minor adjustments to trial processes. The IMP2ART strategy is now being tested in a UK-wide cRCT [ref: ISRCTN15448074], evaluating implementation (action plan ownership) and health outcomes (unscheduled care).

Background:COPD and cardiovascular disease (CVD) are leading causes of death with overlapping and syndemic pathophysiological interactions. Inhaled triple therapies containing inhaled corticosteroids (ICS), long-acting muscarinic antagonists (LAMA) and long-acting β2-agonists (LABA) reduce COPD exacerbation rates and improve lung function versus dual LAMA/LABA therapy. The effect of inhaled triple therapies on combined cardiac and pulmonary (i.e., cardiopulmonary) events in people with COPD and elevated cardiopulmonary risk has not been prospectively tested in randomised clinical trials. Methods:THARROS is a multinational, event-driven cardiopulmonary outcomes trial evaluating budesonide/glycopyrronium/formoterol fumarate dihydrate (BGF) triple therapy versus glycopyrronium/formoterol fumarate dihydrate dual therapy in patients with COPD and elevated cardiopulmonary risk not using ICS-containing maintenance therapy. Eligibility requirements include symptomatic COPD (COPD Assessment Test scores ≥10) without a requirement for prior COPD exacerbations, blood eosinophils ≥100 cells·mm-3, established CVD or CVD risk based on clinical characteristics, clinical risk scores or imaging-based risk criteria. The composite primary end-point is time to first severe cardiac or COPD event and includes three event types, including severe cardiac events (heart failure acute healthcare visit/hospitalisation, myocardial infarction hospitalisation), severe COPD exacerbations and cardiopulmonary death. Approximately 5000 patients will be randomised to achieve 632 participants with ≥1 primary severe adjudicated cardiopulmonary event. Conclusion:This first-of-its-kind cardiopulmonary outcomes trial will determine the effect of BGF on a novel composite end-point comprising severe cardiopulmonary events in a broad COPD population with elevated cardiopulmonary risk not currently using ICS-containing maintenance therapy.

BACKGROUND:Approximately 5% of patients with asthma have severe disease. Treatment escalation may occur despite symptoms not being due to asthma, leading to comorbidities occurring. OBJECTIVE:To explore factors associated with treatment escalation to Global Initiative for Asthma (GINA): step 4/5 in patients with asthma. METHODS:A nested case-control study of patients with asthma from the Optimum Patient Care Research Database. Study 1: patients who transitioned from GINA: steps 2/3 to steps 4/5 were compared with matched controls (GINA: step 2/3). Study 2: patients who transitioned from step 4 to step 5 were compared with matched controls (step 4). RESULTS:Study 1: Step 4/5 cases (n = 12,780) were older, obese, predominantly female, more comorbid (≥2) with increased exacerbations versus step 2/3 controls (n = 31,974) (P < .001). Exacerbations increased nearing treatment escalation in cases but not controls. Study 2: There was no difference in age, sex, or obesity levels in step 5 cases (n = 12,780) versus step 4 controls (n = 31,974). Cases were more comorbid (≥2) (54.0% vs 44.3%, P = .001), with increased mood disorder levels (depression/anxiety) (21.0% vs 13.7%, P = .002) and more exacerbations (81.4% vs 34.3%, P < .001), versus controls. Exacerbations and mood disorder were associated with treatment escalation (P < .001). Mood disorder and exacerbations were more common in cases than in controls, before study entry, but increased in cases alone nearing treatment escalation. CONCLUSIONS:Treatment escalation is associated with mood disorder and asthma exacerbations. Obesity is highly prevalent in patients with asthma before treatment escalation. A symptom-based treatment approach potentially exposes patients to inappropriate treatment escalation.

BACKGROUND:Because the number of monoclonal antibodies available for severe asthma is growing, specialists currently choose without clear guidelines. Despite increasing knowledge on treatment response to these monoclonal antibodies, making the optimal choice for each individual patient remains a challenge. However, evidence of this daily challenge is lacking. OBJECTIVE:To evaluate interobserver agreement on the choice of biologic therapy in severe asthma patients among severe asthma specialists, based on clinical cases. METHODS:This 2-phase study included a pilot local study and an international validation study. Asthma specialists were presented 7 real-life asthma cases managed with a monoclonal antibody. Based on the clinical information provided in the cases, they were asked whether they would have initiated a monoclonal antibody and, if so, their treatment of choice between (1) omalizumab, (2) mepolizumab, (3) reslizumab, (4) benralizumab, and (5) dupilumab. Interobserver agreement for each question was assessed using Gwet agreement coefficient (AC1). RESULTS:Sixteen physicians from the Province of Quebec (Canada) completed the pilot survey, and 70 physicians from 26 countries completed the international survey. The Gwet AC1 for the decision to initiate a biological therapy was 0.48 in the pilot survey and 0.33 in the international survey. For the choice of therapy, agreement was 0.33 and 0.26, respectively. CONCLUSIONS:The interobserver agreement among asthma specialists in both the decision to initiate a biological treatment in patients with severe asthma and the selection of treatment is weak. These results highlight the need for studies seeking reliable predictors for optimal response to biological therapies.